{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "cell_id": "ea14541978434e73a78a4f06f7fe013d",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 25
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 1693,
    "execution_start": 1660021049397,
    "id": "6D611E573E814A688168A45DC3E02A6D",
    "jupyter": {},
    "scrolled": false,
    "slideshow": {
     "slide_type": "slide"
    },
    "source_hash": "94fbf02b",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据集大小： 80\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dataset = np.loadtxt('kmeans_data.csv', delimiter=',')\n",
    "print('数据集大小：', len(dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "cell_id": "4c466dd70ee444279fd37a25e8dadd02",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 31
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 872,
    "execution_start": 1660024565094,
    "scrolled": true,
    "source_hash": "afe9f5a6",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘图函数\n",
    "def show_cluster(dataset, cluster, centroids=None):  \n",
    "    # dataset：数据\n",
    "    # centroids：聚类中心点的坐标\n",
    "    # cluster：每个样本所属聚类\n",
    "    # 不同种类的颜色，用以区分划分的数据的类别\n",
    "    colors = ['blue', 'red', 'green', 'purple']\n",
    "    markers = ['o', '^', 's', 'd']\n",
    "    # 画出所有样例\n",
    "    K = len(np.unique(cluster))\n",
    "    for i in range(K):\n",
    "        plt.scatter(dataset[cluster == i, 0], dataset[cluster == i, 1], \n",
    "            color=colors[i], marker=markers[i])\n",
    "\n",
    "    # 画出中心点\n",
    "    if centroids is not None:\n",
    "        plt.scatter(centroids[:, 0], centroids[:, 1], \n",
    "            color=colors[:K], marker='+', s=150)  \n",
    "        \n",
    "    plt.show()\n",
    "\n",
    "# 初始时不区分类别\n",
    "show_cluster(dataset, np.zeros(len(dataset), dtype=int))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "cell_id": "0b0f3cf7d7524823b9928f02e0775774",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 43
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 7,
    "execution_start": 1660021051460,
    "source_hash": "a7e6ece1",
    "tags": []
   },
   "outputs": [],
   "source": [
    "def random_init(dataset, K):\n",
    "    # 随机选取是不重复的\n",
    "    idx = np.random.choice(np.arange(len(dataset)), size=K, replace=False)\n",
    "    return dataset[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "cell_id": "8c289af0217e41818e60030ec62cc2c3",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 55
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 3,
    "execution_start": 1660021148342,
    "source_hash": "2709f6b1",
    "tags": []
   },
   "outputs": [],
   "source": [
    "def Kmeans(dataset, K, init_cent):\n",
    "    # dataset：数据集\n",
    "    # K：目标聚类数\n",
    "    # init_cent：初始化中心点的函数\n",
    "    centroids = init_cent(dataset, K)\n",
    "    cluster = np.zeros(len(dataset), dtype=int)\n",
    "    changed = True\n",
    "    # 开始迭代\n",
    "    itr = 0\n",
    "    while changed:\n",
    "        changed = False\n",
    "        loss = 0\n",
    "        for i, data in enumerate(dataset):\n",
    "            # 寻找最近的中心点\n",
    "            dis = np.sum((centroids - data) ** 2, axis=-1)\n",
    "            k = np.argmin(dis)\n",
    "            # 更新当前样本所属的聚类\n",
    "            if cluster[i] != k:\n",
    "                cluster[i] = k\n",
    "                changed = True\n",
    "            # 计算损失函数\n",
    "            loss += np.sum((data - centroids[k]) ** 2)\n",
    "        # 绘图\n",
    "        print(f'Iteration {itr}, Loss {loss:.3f}')\n",
    "        show_cluster(dataset, cluster, centroids)\n",
    "        # 更新中心点\n",
    "        for i in range(K):\n",
    "            centroids[i] = np.mean(dataset[cluster == i], axis=0)\n",
    "        itr += 1\n",
    "\n",
    "    return centroids, cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "cell_id": "8c83828ee3304fce968361dd716506c4",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 67
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 1385,
    "execution_start": 1660024568364,
    "source_hash": "35b5a5ad",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0, Loss 711.336\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1, Loss 409.495\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 2, Loss 395.264\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 3, Loss 346.068\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 4, Loss 294.244\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 5, Loss 178.808\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 6, Loss 151.090\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "cent, cluster = Kmeans(dataset, 4, random_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "cell_id": "710ba7fb53394c15aa111db21a3f95f6",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 79
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 3,
    "execution_start": 1660024355859,
    "source_hash": "76ec3d55",
    "tags": []
   },
   "outputs": [],
   "source": [
    "def kmeanspp_init(dataset, K):\n",
    "    # 随机第一个中心点\n",
    "    idx = np.random.choice(np.arange(len(dataset)))\n",
    "    centroids = dataset[idx][None]\n",
    "    for k in range(1, K):\n",
    "        d = []\n",
    "        # 计算每个点到当前中心点的距离\n",
    "        for data in dataset:\n",
    "            dis = np.sum((centroids - data) ** 2, axis=-1)\n",
    "            # 取最短距离的平方\n",
    "            d.append(np.min(dis) ** 2)\n",
    "        # 归一化\n",
    "        d = np.array(d)\n",
    "        d /= np.sum(d)\n",
    "        # 按概率选取下一个中心点\n",
    "        cent_id = np.random.choice(np.arange(len(dataset)), p=d)\n",
    "        cent = dataset[cent_id]\n",
    "        centroids = np.concatenate([centroids, cent[None]], axis=0)\n",
    "\n",
    "    return centroids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "cell_id": "21cdebcd617f4d9b95bb5da4f88f41e5",
    "deepnote_app_coordinates": {
     "h": 5,
     "w": 12,
     "x": 0,
     "y": 91
    },
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 899,
    "execution_start": 1660024579498,
    "source_hash": "13182f7c",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0, Loss 373.939\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1, Loss 158.147\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 2, Loss 151.273\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cent, cluster = Kmeans(dataset, 4, kmeanspp_init)"
   ]
  }
 ],
 "metadata": {
  "deepnote": {},
  "deepnote_app_layout": "article",
  "deepnote_execution_queue": [],
  "deepnote_notebook_id": "60251fe6bfda4aef99382dc3dd589c38",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
